Jul 6, 2026 04:58 PM
AI mistakes can cost doctors time when writing to patients
https://www.eurekalert.org/news-releases/1134481
EXCERPTS: Artificial intelligence is spreading rapidly in health care, with the goal of streamlining critical but onerous clerical tasks such as note-taking and charting so that physicians and nurses can devote more time to patients.
But even when AI can free up doctors to correspond with patients, it may fall short in helping them do it by introducing errors and extraneous details into their messages, according to a new Dartmouth study presented at the 2026 Annual Meeting of the Association for Computational Linguistics and published in the conference proceedings.
The result is that physicians may spend more time editing responses than it would've taken to write them, the researchers report. "We find that AI can sound like a doctor but not think like one," says Sarah Preum, an assistant professor of computer science and the study's co-corresponding author with Parker Seegmiller, a graduate researcher in Preum's PersistLab at Dartmouth.
[...] The team reports that AI-generated answers frequently misalign with what clinicians would actually write. This includes automated responses that are too long, don't ask follow-up questions, and use irrelevant or inaccurate medical details.
"There are smaller studies that say, 'Oh, AI is amazing,' but we realized there is a gap in the existing literature of a large-scale evaluation of this technology," Preum says. "We didn't just want to measure a platform's accuracy, but whether it actually helps with the workload, which in this case is measured by how much editing the physician is doing."
[...] The researchers show, however, that adapting AI to how individual physicians communicate can improve accuracy by 33% and reduce editing by 26%.
"If message generation is really efficient and high quality, if it asks the right things, then it really has potential to improve efficiency," says co-author Tim Burdick, an associate professor of community and family medicine in Dartmouth's Geisel School of Medicine and a family medicine physician at Dartmouth Health.
"I don't foresee a time when the portal can respond to a patient without a clinician editing it first. But as we make the models better, we'll be able to address portal messages much more quickly and with less mental energy," Burdick says.
The study shows that there are such things as "good" AI responses and provides a framework for implementing them into patient-physician portals, Preum says. These platforms are increasingly common among large health care systems and often customized, she says... (MORE - missing details, no ads)
https://www.eurekalert.org/news-releases/1134481
EXCERPTS: Artificial intelligence is spreading rapidly in health care, with the goal of streamlining critical but onerous clerical tasks such as note-taking and charting so that physicians and nurses can devote more time to patients.
But even when AI can free up doctors to correspond with patients, it may fall short in helping them do it by introducing errors and extraneous details into their messages, according to a new Dartmouth study presented at the 2026 Annual Meeting of the Association for Computational Linguistics and published in the conference proceedings.
The result is that physicians may spend more time editing responses than it would've taken to write them, the researchers report. "We find that AI can sound like a doctor but not think like one," says Sarah Preum, an assistant professor of computer science and the study's co-corresponding author with Parker Seegmiller, a graduate researcher in Preum's PersistLab at Dartmouth.
[...] The team reports that AI-generated answers frequently misalign with what clinicians would actually write. This includes automated responses that are too long, don't ask follow-up questions, and use irrelevant or inaccurate medical details.
"There are smaller studies that say, 'Oh, AI is amazing,' but we realized there is a gap in the existing literature of a large-scale evaluation of this technology," Preum says. "We didn't just want to measure a platform's accuracy, but whether it actually helps with the workload, which in this case is measured by how much editing the physician is doing."
[...] The researchers show, however, that adapting AI to how individual physicians communicate can improve accuracy by 33% and reduce editing by 26%.
"If message generation is really efficient and high quality, if it asks the right things, then it really has potential to improve efficiency," says co-author Tim Burdick, an associate professor of community and family medicine in Dartmouth's Geisel School of Medicine and a family medicine physician at Dartmouth Health.
"I don't foresee a time when the portal can respond to a patient without a clinician editing it first. But as we make the models better, we'll be able to address portal messages much more quickly and with less mental energy," Burdick says.
The study shows that there are such things as "good" AI responses and provides a framework for implementing them into patient-physician portals, Preum says. These platforms are increasingly common among large health care systems and often customized, she says... (MORE - missing details, no ads)